用量子逻辑框架统一建模记忆随时间的衰减与重构过程。
Temporal Model On Quantum Logic
- 结合时序逻辑与贝叶斯更新，构建分层记忆演化模型。
- 引入熵衡量回忆效率，揭示记忆链的递归影响机制。
- 适用于认知科学与神经计算交叉研究者。
本文提出一个统一的理论框架，用于建模时序记忆动态，融合时序逻辑、记忆衰减模型与分层上下文概念。该框架通过线性与分支时序模型形式化命题随时间的演化，引入指数衰减（艾宾浩斯遗忘曲线）和贝叶斯更新驱动的再激活机制。记忆的分层组织由有向无环图表示，以建模回忆依赖关系与干扰。新发现包括反馈动态、记忆链中的递归影响以及基于熵的回忆效率整合。该方法为理解认知与计算领域中的记忆过程提供了基础。
原文摘要 · Abstract (English)
This paper introduces a unified theoretical framework for modeling temporal memory dynamics, combining concepts from temporal logic, memory decay models, and hierarchical contexts. The framework formalizes the evolution of propositions over time using linear and branching temporal models, incorporating exponential decay (Ebbinghaus forgetting curve) and reactivation mechanisms via Bayesian updating. The hierarchical organization of memory is represented using directed acyclic graphs to model recall dependencies and interference. Novel insights include feedback dynamics, recursive influences in memory chains, and the integration of entropy-based recall efficiency. This approach provides a foundation for understanding memory processes across cognitive and computational domains.
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